1. Field of the Invention
The invention generally relates to a gait perturbation system. More particularly, the invention relates to a gait perturbation system that is capable of perturbing a gait of a person.
2. Background and Description of Related Art
In order to study human motion, subjects are often tested in gait labs which are provided with special equipment disposed therein for measuring body movements, body mechanics, and/or the activity of the muscles (e.g., gait labs with force plates, etc.). The gait analysis performed in the gait lab is typically used to assess, plan, and/or treat subjects with medical conditions affecting their ability to walk. Also, the gait analysis is often used in sports biomechanics to improve athletic performance, and to help identify and/or treat injuries that deleteriously affect athletic performance.
However, the artificial nature of a typical environment for testing and/or training the gait of a subject (e.g., a typical gait lab) makes it difficult to simulate the real-life conditions that are encountered by the subject. Also, these artificial environments for gait testing and/or training are unable to effectively simulate the uncertain nature of the stimuli encountered by subjects in real-life scenarios. As such, these artificial gait testing and/or training environments are limited in their overall ability to effectively test and/or train subjects for the scenarios that are actually experienced by subjects in the their everyday lives.
Therefore, what is needed is a gait perturbation system that is capable of simulating real-life conditions by subjecting the person being tested to dynamic instability. Moreover, a gait perturbation system is needed that is capable of generating random stimuli in order to emulate real-life conditions encountered by the person undergoing testing. Furthermore, what is needed is a gait perturbation system that is capable of more effectively training a person with a gait disorder by delivering random stimuli to the person so that he or she is able to more effectively react to unpredictable disturbances that are encountered in real-life scenarios.